Top Senior Level Jobs in Kansas City, MO

Administer and maintain enterprise file transfer platforms (IBM Sterling, Axway), ensure secure, reliable transfers, troubleshoot failures, perform upgrades/patches, automate workflows with scripts and Ansible, provide on-call production support, manage security controls and compliance, and create technical documentation and runbooks.

Configure, maintain, test, analyze and troubleshoot business application systems for Federal Reserve payment services. Manage customer setups, account/settlement relationships, investigate complex production issues (including cyber incidents), coordinate stakeholders, lead projects and testing, provide training and documentation, and meet SLAs for Fedwire, FedNow and related systems.

Leads a data science team focused on customer intelligence and personalization across digital products, apps, newsletters, and marketing channels. Develops lifetime value, segmentation, retention, recommendation, attribution, forecasting, and engagement models. Owns product funnel analytics and experimentation, including A/B testing and causal inference. Partners with Product, Marketing, Editorial, Data Operations, and Engineering to translate customer behavior into product improvements, measurable growth, and scalable data capabilities.

Drive profitable growth for middle-market construction casualty accounts in the Midwest by selecting risks, underwriting and pricing policies, managing a complex portfolio, building broker relationships, documenting decisions, mentoring junior underwriters, and participating in continuous improvement and marketing efforts.

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Own GTM performance analytics, KPI and target setting, reporting, forecasting, compensation planning, and performance reviews across Sales and Post-Sales. Identify anomalies and optimization opportunities involving conversion, churn, productivity, pricing, packaging, segmentation, channel economics, and customer quality. Partner with Finance and GTM leaders to develop recommendations, lead strategic initiatives, and ensure data integrity while translating analysis into actionable business decisions.

Leads and scales Advisory, Delivery, and Support workstreams across a distributed technical services organization. Establishes shared operating standards, capacity planning, quality controls, SLAs, escalation processes, reporting, and governance. Oversees technical delivery outcomes, resource allocation, architecture quality, support coverage, hiring plans, onboarding, and partner collaboration. Partners with Enablement, Sales, Project Managers, and SI/GSI organizations to improve delivery predictability, utilization, client satisfaction, and technical excellence.

Designs and operates batch, streaming, and real-time data platforms and pipelines using Spark, Kafka, Iceberg, Airflow, and cloud infrastructure. Owns data lake evolution, data quality, observability, reliability, governance, event instrumentation, schema management, and privacy controls for PII, retention, deletion, and residency. Leads complex initiatives end-to-end, troubleshoots production issues, mentors engineers, and develops AI agent harnesses that enforce data engineering standards and quality gates.

Design and lead the technical strategy for search across Vannevar’s products. Build and improve full-text, vector, and LLM-powered retrieval systems, optimizing latency, relevance, index quality, freshness, and performance. Collaborate with ML, product, design, and mission strategy teams to translate user needs into search innovations. Apply expertise in information retrieval, NLP, machine learning, indexing, ranking, query parsing, tokenization, vector search, and evaluation frameworks.